基于双树复小波变换和形态滤波的PPG信号去噪方法

A Hybrid Denoising Method for PPG Signal Based on Dual Tree Complex Wavelet Transform and Morphological Filtering

脉搏信号包含大量的噪声,具有强烈的非线性和非平稳性。针对传统的小波变换去噪算法的缺陷,本文提出了一种基于双树复小波变换和形态滤波的去噪算法,具有结构简单、数学含义清晰及计算复杂度低等优点,有效的克服了离散小波变换的平移敏感性和频率混淆。实验表明,该算法可以有效的去除脉搏信号中工频干扰及肌电干扰等高频噪声,其信噪比及均方差等定量指标均明显优于传统的阈值去噪算法,能得到较干净的脉搏信号波形。

The pulse signal contains a lot of noise and therefore has strong nonlinear and non-stationary. Aiming at the defects of traditional wavelet transform denoising method, this paper proposes a denoising algorithm based on the dual tree complex wavelet transform and morphological filtering which has the advantages of simple structure, clear mathematical meaning and low computational complexity, effectively overcomes the translation sensitivity and frequency confusion of discrete wavelet transform. Experiments show that the proposed algorithm can effectively remove the high frequency noise of pulse signal such as the power frequency interference and the myoelectricity interference, has the better quantitative indicators such as signal-to-noise ratio and mean square error than the traditional threshold denoising algorithm. Therefore, a clean pulse signal waveform can be obtained.